Super-resolution of a video image refers to a technology of obtaining a high-resolution video image through corresponding processing by using a low-resolution video image. The super-resolution technology is widely applied in many scenarios and has important application values and market prospects in fields such as high-definition TV, mobile communication, image and video compression technologies, social security, video surveillance, graphic rendering, image inpainting, biometric authentication, and satellite and astronomical images. Therefore, a method for implementing super-resolution on a video image is especially important.
At present, super-resolution methods for a video image mainly include: a super-resolution method based on interpolation, where in the method, generally, known points in a low-resolution video image are used to interpolate an unknown point in a high-resolution video image by using a specific function relationship, so that the high-resolution video image is obtained; and a super-resolution method based on fuzzy motion estimation, where the method uses a large amount of redundant information existing in an image either in space or in time to find many similar blocks in a current frame and a frame adjacent to the current frame, assigns a weight to each similar block according to a difference, and then performs a multiply-accumulate operation on points in the low-resolution video image to which these similar blocks are mapped and the assigned weights, so as to obtain new values of points in the high-resolution video image.
During the implementation of the present invention, it is found that the prior art has at least the following problems.
The super-resolution method based on interpolation is based merely on image pixel values, where a problem of blurring and jagged edges may easily occur when a magnification is large (greater than 2), and an effect of super-resolution sharpening can hardly be achieved. In the super-resolution method based on fuzzy motion estimation, when weighted accumulation is performed on points in a low-resolution video image to which similar blocks are mapped and weights, a coordinate mapping relationship between a point in a high-resolution video image and a point in the low-resolution video image needs to be used, where for super-resolution by non-integral multiple times, a point in the low-resolution video image cannot be accurately mapped to the high-resolution video image.